General incremental sliding-window aggregation
نویسندگان
چکیده
منابع مشابه
General Incremental Sliding-Window Aggregation
Stream processing is gaining importance as more data becomes available in the form of continuous streams and companies compete to promptly extract insights from them. In such applications, sliding-window aggregation is a central operator, and incremental aggregation helps avoid the performance penalty of re-aggregating from scratch for each window change. This paper presents Reactive Aggregator...
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Let f : R → [r] = {1, 2, . . . , r} be a measurable function, and let {Ui}i∈N be a sequence of i.i.d. random variables. Consider the random process Zi = f(Ui, ..., Ui+k−1). We show that for all q, there is a positive probability, uniform in f , that Z1 = Z2 = ... = Zq. A continuous counterpart is that if f : R → R, and Ui and Zi are as before, then there is a positive probability, uniform in f ...
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Sliding-window computations are widely used for data analysis in networked systems. Such computations can consume significant computational resources, particularly in live systems, where new data arrives continuously. This is because they typically require a complete re-computation over the full window of data every time the window slides. Therefore, sliding-window computations face important s...
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ژورنال
عنوان ژورنال: Proceedings of the VLDB Endowment
سال: 2015
ISSN: 2150-8097
DOI: 10.14778/2752939.2752940